Visualization of genetic disease-phenotype similarities by multiple maps t-SNE with Laplacian regularization.

ABSTRACT:

Background

From a phenotypic standpoint, certain types of diseases may prove to be difficult to accurately diagnose, due to specific combinations of confounding symptoms. Referred to as phenotypic overlap, these sets of disease-related symptoms suggest shared pathophysiological mechanisms. Few attempts have been made to visualize the phenotypic relationships between different human diseases from a machine learning perspective. The proposed research, it is anticipated, will visually assist researchers in quickly disambiguating symptoms which can confound the timely and accurate diagnosis of a disease.

Methods

Our method is primarily based on multiple maps t-SNE (mm-tSNE), which is a probabilistic method for visualizing data points in multiple low dimensional spaces. We improv

SUBMITTER: Xu W 

PROVIDER: S-EPMC4243097 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature